Autonomous Ultrasound

Autonomous ultrasound aims to automate the process of ultrasound scanning, reducing reliance on expert sonographers and improving accessibility to this vital imaging modality. Current research focuses on developing intelligent systems that can plan and execute scans autonomously, often employing machine learning techniques such as Bayesian optimization and graph-based registration to adapt to individual patient anatomy and achieve accurate probe positioning. These advancements leverage computer vision, large language models, and multimodal data integration to improve scan efficiency and image quality, potentially leading to faster, more consistent, and widely available diagnostic imaging.